# Ananya Mote

> DataScientist | ML / AI Engineer | Agentic AI | NLP | Gen AI | LLMs | Python, R , SQL | MySQL, PostgreSQL | Aws, Azure | Pyspark | PowerBI, Tableau |

Location: Houston, Texas, United States
Profile: https://flows.cv/ananyamote

AI Engineer with 3+ years of experience building intelligent systems, scalable pipelines, and AI-driven solutions that accelerate digital transformation in retail and e-commerce. Proficient in Python, SQL, Spark, and deep learning frameworks like PyTorch and TensorFlow, with specialized expertise in NLP, LLMs, OCR, and computer vision. Skilled in deploying secure, reproducible models on AWS, Azure, and GCP, supported by strong MLOps practices. Recognized for problem-solving, collaboration, and stakeholder communication, I deliver impactful AI innovations that optimize operations, enhance customer engagement, and enable data-driven decision-making across enterprise markets.

## Work Experience
### AI Engineer @ Walmart
Jan 2024 – Present | United States
•	Online conversion rates improved by 15% after deploying a dynamic pricing engine leveraging Python, SQL, and Scikit-learn to analyze competitive benchmarks, seasonal demand, and customer purchasing behaviors.
•	Walmart’s mobile app engagement rose 19% through personalized recommendation systems powered by PyTorch, Transformers, and TensorFlow, delivering relevant cross-category suggestions.
•	Negative review visibility was reduced 31% when NLP models built with Hugging Face Transformers, SpaCy, and BERT processed millions of e-commerce reviews, refining product quality insights and customer trust.
•	Checkout completion increased 12% after implementing A/B testing frameworks on AWS SageMaker and Vertex AI, optimizing personalized payment options, promotions, and simplified checkout flows across Walmart.com.
•	Real-time customer journey tracking was enabled by Snowflake, Databricks, and Airflow, integrating browsing, cart, and purchase datasets, delivering actionable campaign insights that improved digital marketing ROI by 22%.
•	Executives gained instant visibility into e-commerce KPIs through interactive dashboards designed in Tableau supporting faster merchandising, pricing, and campaign decisions with 17% improved profitability.

### Data Scientist @ Reliance Retail
Jan 2022 – Jan 2023 | India
•	Built real-time sales monitoring pipelines using Python, Spark Streaming, and Airflow, integrating 2.1TB daily POS data, improving retail decision-making speed by 43% across multiple Reliance store clusters.
•	Developed computer vision models with TensorFlow, PyTorch, and OpenCV, automating shelf stock detection in retail outlets, reducing manual audits by 62% and ensuring timely replenishment across high-demand categories.
•	Implemented recommendation engines using Scikit-learn, XGBoost, and collaborative filtering, improving cross-selling conversion rates by 25%, enhancing customer experience in both e-commerce platforms and physical Reliance stores.
•	Orchestrated supply chain ETL workflows with Databricks, Delta Lake, and Snowflake, consolidating procurement and logistics data, improving retail vendor performance tracking and reducing distribution delays by 18%.
•	Deployed time-series forecasting pipelines on AWS SageMaker and Azure ML, predicting festival season demand surges, enabling proactive inventory allocation, and cutting stock-out incidents by 29% across Hyderabad region stores.
•	Designed retail analytics dashboards in Power BI visualizing SKU-level sales, promotions, and footfall trends, enabling retail executives to optimize campaign spending and drive 20% higher ROI.

### Data Scientist @ Reliance Retail
Jan 2021 – Jan 2022 | India


## Education
### Masters in Information Sciences in Data Science
University of Houston-Clear Lake

### Bachelors of Engineering in Information Technology
Vasavi College of Engg


## Contact & Social
- LinkedIn: https://linkedin.com/in/ananyamote

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Source: https://flows.cv/ananyamote
JSON Resume: https://flows.cv/ananyamote/resume.json
Last updated: 2026-04-17